Triple
T19822668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huvudsta metro station |
E476234
|
entity |
| Predicate | hasStationCode |
P1289
|
FINISHED |
| Object |
HUV
HUV is the station code for Huvudsta metro station on the Stockholm metro system in Sweden.
|
E1397458
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: HUV | Statement: [Huvudsta metro station, hasStationCode, HUV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HUV Context triple: [Huvudsta metro station, hasStationCode, HUV]
-
A.
HVF
HVF is a data-focused startup and innovation lab created by entrepreneur Max Levchin to explore and build companies around large-scale data problems.
-
B.
HVF
HVF is the National Rail station code for Haverfordwest railway station in Pembrokeshire, Wales.
-
C.
Hov
Hov is a small coastal village on the island of Gimsøya in Norway’s Lofoten archipelago, known for its scenic beaches, golf course, and views of the midnight sun and Northern Lights.
-
D.
Hov
Hov is a small village on the Faroe Islands' southernmost island of Suðuroy, known for its coastal setting and traditional Faroese character.
-
E.
Hov
Hov is a small village in Innlandet county, Norway, serving as the main local hub for services and commerce in the Søndre Land area.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: HUV Triple: [Huvudsta metro station, hasStationCode, HUV]
Generated description
HUV is the station code for Huvudsta metro station on the Stockholm metro system in Sweden.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HUV Target entity description: HUV is the station code for Huvudsta metro station on the Stockholm metro system in Sweden.
-
A.
HVF
HVF is a data-focused startup and innovation lab created by entrepreneur Max Levchin to explore and build companies around large-scale data problems.
-
B.
HVF
HVF is the National Rail station code for Haverfordwest railway station in Pembrokeshire, Wales.
-
C.
Hov
Hov is a small village in Innlandet county, Norway, serving as the main local hub for services and commerce in the Søndre Land area.
-
D.
Hov
Hov is a small coastal village on the island of Gimsøya in Norway’s Lofoten archipelago, known for its scenic beaches, golf course, and views of the midnight sun and Northern Lights.
-
E.
Hov
Hov is a small village on the Faroe Islands' southernmost island of Suðuroy, known for its coastal setting and traditional Faroese character.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e51c7c188190b926f3a2a7b5f881 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e654ffb37c8190be540a793befe16c |
completed | April 20, 2026, 4:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07ccd22b448190b447c893ee9ffd83 |
completed | May 16, 2026, 1:48 a.m. |
| NEDg | Description generation | batch_6a07cfe19c288190b360d1767e8fffa3 |
completed | May 16, 2026, 2:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07d0c1cbc08190bffbc27457117b82 |
completed | May 16, 2026, 2:04 a.m. |
Created at: April 10, 2026, 1:50 p.m.